Ripple Effects of Climate Change

Header 2: some background and context

Research Questions

The questions we plan to investigate are the following:

  1. Bella’s question
  2. Mythili’s question
  3. Lillian’s question

Header 3

This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For example, you can include Bold and Italic and Code text. For more details on using R Markdown see http://rmarkdown.rstudio.com.

You should test out updating your GitHub Pages website:

  • clone your group’s blog project repo in RStudio
  • update “Your Project Title Here” to a new title in the YAML header
  • knit index.Rmd
  • commit and push BOTH the index.Rmd and the index.html files
  • go to https://stat231-f20.github.io/Blog-HealthAndJusticeLeague to see the published test document (this is publicly available!)

Including code and plots

You can embed code as normal, for example:

summary(cars)
##      speed           dist       
##  Min.   : 4.0   Min.   :  2.00  
##  1st Qu.:12.0   1st Qu.: 26.00  
##  Median :15.0   Median : 36.00  
##  Mean   :15.4   Mean   : 42.98  
##  3rd Qu.:19.0   3rd Qu.: 56.00  
##  Max.   :25.0   Max.   :120.00

Let’s clean up the format of that output:

Speed Distance
Min. : 4.0 Min. : 2.00
1st Qu.:12.0 1st Qu.: 26.00
Median :15.0 Median : 36.00
Mean :15.4 Mean : 42.98
3rd Qu.:19.0 3rd Qu.: 56.00
Max. :25.0 Max. :120.00

In a study from the 1920s, fifty cars were used to see how the speed of the car and the distance taken to stop were related. Speeds ranged between 4 and 25 mph. Distances taken to stop ranged between 2 and 120 feet, with the middle 50% falling between 26 and 56 feet.

You can also embed plots as normal, for example:

Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.

Bulleted list

You can make a bulleted list like this:

  • item 1
  • item 2
  • item 3

Numbered list

You can make a numbered list like this

  1. First thing I want to say
  2. Second thing I want to say
  3. Third thing I want to say

Tab 1: Bella’s part

#PM2.5 leaflets
PM25_1990_leaflet
PM25_2017_leaflet
PM25_change_leaflet
DALY_1990_leaflet
DALY_2017_leaflet
DALY_change_leaflet
animate(g, duration = 20, fps = 20, width = 400, height = 400, renderer = gifski_renderer())

#anim_save("PM2.5 vs. DALY.gif")
gdaly
gexposure

Tab 2: Mythili’s part

path_mythili <- "C:/Users/seshu/Documents/RStudio/projects/git/Blog-HealthAndJusticeLeague/data"

#loading data
data_cluster1980s <- read_csv(paste0(path_bella,"/wrangled_infmatmortcluster1980s.csv")) %>%
  mutate_at(c("avginfmort", "avmatmort"), funs(`std`=scale(.) %>% as.vector()))
## Parsed with column specification:
## cols(
##   COU = col_character(),
##   Country = col_character(),
##   decade = col_double(),
##   avginfmort = col_double(),
##   avmatmort = col_double()
## )
#making cluster reproducible, setting number of clusters
set.seed(23)
km_out <- kmeans(data_cluster1980s[,c("avginfmort_std", "avmatmort_std")], centers=4, nstart=20)
##  [1] 2 2 2 2 2 1 4 2 2 4 2 2 2 4 4 2 2 2 2 2 4 2 3 2 2 2 4 4 4 2 2 2
# visualize the cluster assignments and centroids
ggplot(data = cluster1980s, aes(x = avginfmort_std, y = avmatmort_std)) + 
  geom_point(aes(color = clust)) +
  #geom_text_repel(aes(label= `Country`, color = clust), size = 3) +
  coord_fixed() +
  geom_point(data = as.data.frame(km_out$centers)
             , aes(x = avginfmort_std, y = avmatmort_std)
             , pch = "X"
             , size = 4) +
  labs(x = "Average Infant Mortality in 1980s"
       , y = "Average Maternal Mortality in 1980s" 
       , color = "Cluster Assignment")

Tab 3: Lillian’s part

Here, I am investigating how the impacts of natural disasters have changed over time since 1980 until 2020. Specifically, how has the frequency of natural disasters changed? How has the number of people killed, injured, affected, and displaced due to these disasters changed?
To investigate this problem, take a look at the shiny app below.